AbstrakPertumbuhan populasi penduduk karena perkembangan industri di Indonesia memberikan dampak negatif terhadap sumber daya hutan. Pada penelitian ini bertujuan untuk menganalisis kerusakan hutan dengan adanya pengaruh laju pertumbuhan penduduk karena faktor migrasi penduduk. Permasalahan tersebut kemudian diformulasikan ke dalam bentuk model matematika dan dianalisis kestabilan sistemnya. Persamaan model matematika ini merupakan sistem persamaan diferensial nonlinier. Kestabilan sistem diperoleh dengan menganut kriteria Routh-Hurwitz. Selanjutnya, dari titik kesetimbangan yang diperoleh dilakukan simulasi numerik. Pada hasil numerik menunjukkan terjadinya peningkatan kesetimbangan dari populasi penduduk dan industrialisasi yang mengakibatkan tingkat kesetimbangan biomassa hutan mengalami penurunan. Populasi memiliki dampak besar terhadap ekologi stabilitas sehingga dilakukan pengendalian terhadap pertumbuhan populasi atau untuk melindungi sumber daya hutan dari kepunahan. Katakunci: Analisis Kestabilan, Sumber Daya Hutan, Industri Abstract Population growth due to industrial development in Indonesia has a negative impact on forest resources. In this study aims to analyze the damage to the forest with the influence of population growth due to migration. The problem was then formulated into a mathematical model and analyzed the stability of the system. The equation of this mathematical model is
The flow of data and information is growing rapidly and rapidly in various sizes and means which is called Big Data. In the face of a change for the better in the future, a careful analysis and design of a data processing system is needed, in which a predictive framework can formulate the right policy to be one of the efforts to make a good decision. This is one of the appropriate Big Data processing efforts, which can be realized through one of the methods, namely prediction or forecasting is an effort to predict future values or trends as a reference for analyzing conditions in the past. One example of Big Data in the City of Balikpapan, namely the temperature within 2 meters obtained from the NASA satellite published on the website power.larc.nasa.gov. One of the methods used in this research is the ARIMA method and it is developed according to the data used. Based on the data to be used, namely temperature data within a distance of 2 meters in the city of Balikpapan, the development of data processing is carried out to pay attention to three seasonal patterns or the so-called Triple Seasonal ARIMA model. In this study, it can be seen how to build the Triple Seasonal ARIMA model and comparison with alternative models, namely Seasonal ARIMA and Double Seasonal ARIMA, and can see how the results of the Triple Seasonal ARIMA model accuracy when compared with alternative models. The method used in this study is the Seasonal ARIMA, Double Seasonal ARIMA and Triple Seasonal ARIMA methods. The results obtained in this study obtained a comparison of methods in making predictions with a specified time span, the results obtained from the Seasonal ARIMA model that it was very good at predicting a time span of 2 weeks, Double Seasonal ARIMA for a period of 1 month, Double Seasonal ARIMA for a period of 3 months, and Triple Seasonal ARIMA for a period of 6 months.
As a petroleum-producing country, Indonesia has a very important role in supplying national and international petroleum needs. The distribution of oil by sea raises the risk of spills and harms the marine environment, especially for marine life. Most oil spills in the marine environment can form a thin layer on the surface due to the movement of wind, waves, and currents. In this study, the oil spill movement model used the Shallow Water Equation (SWE) model and the equation for the movement of oil spills. The SWE model consists of the equation of mass and momentum derived from the law of conservation of mass which is derived into the equation of continuity and the law of conservation of momentum which is derived into the equation of conservation of momentum. In this model, ocean currents are affected by several disturbances in the form of wind gusts and friction with the bottom. The model is solved numerically through simulation using the finite volume method. Discretization is done by using a staggered grid approach, where the mass and momentum variables are discretized in different cells. From the simulation results, it appears that the movement of oil spills is influenced by wind direction and current. The simulation results also found that the speed of the movement of oil spills has increased in the early times, but then gradually.
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